An anesthesia-integrated model for predicting postoperative urinary retention after transurethral resection of the prostate: A retrospective cohort study
Aug 2026· Journal of International Medical Research· Vol 54· 0 citations· 24 references
Medicine
TL;DR
The proposed anesthesia-integrated model may help identify transurethral resection of the prostate patients at increased risk of postoperative urinary retention and guide individualized perioperative bladder management.
Abstract
Objective To develop and internally validate an anesthesia-integrated prediction model for postoperative urinary retention after transurethral resection of the prostate. Methods This retrospective cohort study included 183 male patients who underwent elective transurethral resection of the prostate between January 2021 and December 2024. The primary endpoint was postoperative urinary retention occurrence within 24 h following catheter removal. Thirty-five candidate predictors spanning four domains were evaluated. Variable selection was performed using least absolute shrinkage and selection operator regression, followed by multivariable logistic regression. Model performance was assessed using the area under the receiver operating characteristic curve, calibration analysis, Brier score, bootstrap internal validation with 1000 resamples, and decision curve analysis. Results Among the 183 patients, 39 (21.3%) developed postoperative urinary retention. Seven least absolute shrinkage and selection operator–selected predictors were retained in the final model, including preoperative postvoid residual volume, history of acute urinary retention, prostate volume, high spinal block level, intraoperative opioid dose (morphine equivalent), catheter indwelling duration, and diabetes mellitus. The model achieved an area under the receiver operating characteristic curve of 0.813 in the training set and a mean bootstrap-validated area under the receiver operating characteristic curve of 0.749 (95% confidence interval: 0.625, 0.860; optimism-corrected area under the receiver operating characteristic curve: 0.731). The Brier score was 0.1287, and the calibration curve demonstrated satisfactory agreement between predicted and observed probabilities. Decision curve analysis suggested the model's clinical net benefit across a broad range of threshold probabilities. Conclusion The proposed anesthesia-integrated model may help identify transurethral resection of the prostate patients at increased risk of postoperative urinary retention and guide individualized perioperative bladder management. Prospective, multicenter external validation is warranted prior to clinical implementation.
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Background Anastomotic leakage (AL) remains a severe complication after radical surgery for rectal cancer. Current prediction models rely mainly on static variables and may not capture evolving perioperative physiological stress. This study developed and validated a twostage landmark-based dynamic prediction model that...
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INTRODUCTION
Perioperative bleeding is a clinically important adverse outcome of transurethral resection of the prostate (TURP), the gold standard surgical procedure in the management of benign prostatic hyperplasia (BPH). The difficulty in quantifying blood loss is because there is constant irrigation in the procedure...
S. Fakhralddin· Archivio Italiano di Urologi...· 0 citations
BACKGROUND
Transurethral resection of the prostate (TURP) is the gold standard surgical treatment for benign prostatic hyperplasia (BPH), but postoperative outcomes may differ in patients presenting with acute urinary retention (AUR).
AIM
This study aimed to evaluate the impact of AUR on postoperative outcomes and co...
Y. Aktaş, A. Tongal, A. Gökcan et al.· Nigerian Journal of Clinical...· 0 citations
PURPOSE
Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following...
Bo-han Lin, Yang-Hua Chen, Zhi-Bin Ke et al.· International Brazilian Jour...· 1 citation
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